Advanced Computing, Mathematics and Data Research Highlights

April 2018

Award-winning CCSI Toolset Gets Open-Source Release on GitHub

Last month, the Carbon Capture Simulation Initiative, known as CCSI, released the CCSI Toolset, a computational tools and models suite designed to maximize learning and reduce risk during the scale-up process for carbon capture technologies used by power plants, as open-source software now available on GitHub. CCSI is a partnership led by the National Energy Technology Laboratory for the U.S Department of Energy’s Office of Fossil Energy. Along with NETL, Lawrence Berkeley, Lawrence Livermore, Los Alamos, and Pacific Northwest national laboratories collaborate on the project with academic partners that include Boston University, Carnegie Mellon University, Princeton University, West Virginia University, and the University of Texas. In 20016, the CCSI Toolset was awarded a prestigious R&D 100 Award by R&D Magazine.

CCSI2 extends the initial CCSI project to further accelerate the commercialization of carbon capture technologies.

At PNNL, Zhijie (Jay) Xu, an engineer with ACMD Division’s Computational Mathematics group, leads CCSI’s computational fluid dynamics (CFD) team that develops multiscale CFD models required to simulate the complex physical and chemical processes of carbon capture. The team, which includes Jie Bao, a research engineer with the Computational Fluids and Nuclear Processes group (Energy and Environment Directorate), and Rajesh Singh and Chao Wang, both scientists with ACMD Division’s Computational Engineering group, uses these models to gain insights on flow field and reaction behaviors in laboratory- and device-scale reactors. Primarily, the CFD team focuses on modeling various sorbent, solvent-based, and other emerging capture technologies.

“High-fidelity CFD models with validated and quantified confidence are important for a better understating of the science behind—and are useful for—system-level carbon capture technology designs.” Xu explained. “For example, with our CFD models at different scales, we were able to improve our fundamental understanding of diverse carbon capture technologies and provide predictions with quantified confidence at different levels.”

The open-source CCSI Toolset provides several major capabilities, including rapid computational screening at various scales, accelerated design and evaluation to better understand and improve system performance, and risk management via simulations that consider model and parameter uncertainty and identify and incorporate critical data.

By sharing the toolset via GitHub, CCSI expects that the broader energy technology development community now will be able to expand the software by directly engaging and improving its existing features, as well as adding new ones, and helping to flag and resolve bugs.

The CCSI Toolset also is a critical component of the extended Carbon Capture Simulation for Industry Impact project, or CCSI2, which includes national laboratories, academia, and industry partners.

Acknowledgment:
This research is sponsored by DOE’s Office of Fossil Energy through the Carbon Capture Simulation Initiative.